文章目錄

前言

1 安裝 RPLidar 和 Pixhawk

2 檢查 RPLidar 的串行端口

3 安裝更多軟件包

4 創建Catkin工作空間

5 安裝 RPLidar 節點

6 安裝 Google Cartographer

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前言

本頁展示了如何使用 RPLidarA2 激光雷達(RPLidarA2 lidar)設置 ROS 和 Google Cartographer SLAM，為 ArduPilot 提供本地位置估計，使其可以在沒有 GPS 的情況下運行。

這些說明在使用 APSync 更新的 NVidia TX2 上進行了測試，然后按照此處所述安裝(installed as described here)了 ROS 和 MAVROS。

！Note

這些頁面正在制作中。

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1 安裝 RPLidar 和 Pixhawk

應調整 RPLidar 的方向，使其 USB 調試線線與飛行控制器上的箭頭方向一致。

USB 調試線應插入運行 ROS 的配套計算機的 USB 端口。

2 檢查 RPLidar 的串行端口

將 RPLidarA2 插入配套計算機。如果使用安裝在 AUVidea J120 電路板上的 TX2，請確保將激光雷達插入下方的 USB 端口。

ls -l /dev/tty*

激光雷達應該顯示為 /dev/ttyUSB0 或 /dev/ttyACM0。

如果輸入“lsusb”，設備也應顯示為 "Cygnal Integrated Products, Inc. CP210x UART 橋接器 / myAVR mySmartUSB light"。

根據上面找到的串行端口，只需輸入以下兩條命令中的一條，就可以讀取設備信息：

sudo usermod -a -G dialout

3 安裝更多軟件包

完整安裝 ROS 桌面：

sudo apt-get install ros-<distro>-desktop

或安裝這些單獨的軟件包（此列表尚不完整）：

sudo apt-get install ros-<distro>-tf ros-<distro>-tf-conversions ros-<distro>-laser-geometry

sudo apt-get install ros-<distro>-cv-bridge ros-<distro>-image-transport

sudo apt-get install qt4-qmake qt4-dev-tools

sudo apt-get install protobuf-compiler

4 創建Catkin工作空間

在你的主目錄中：

cd $HOME

mkdir -p catkin_ws/src

cd catkin_ws

catkin_init_workspace

5 安裝 RPLidar 節點

在工作區安裝 RPLidar 節點：

cd $HOME/catkin_ws/src

git clone https://github.com/Slamtec/rplidar_ros.git

6 安裝 Google Cartographer

安裝更多軟件包：

sudo apt-get install python-wstool python-rosdep ninja-build

使用 wstool 重新初始化工作區，然后合并 cartographer_ros.rosinstall 文件并獲取依賴代碼。

cd $HOME/catkin_ws

wstool init src

wstool merge -t src https://raw.githubusercontent.com/googlecartographer/cartographer_ros/master/cartographer_ros.rosinstall

wstool update -t src

安裝 proto3 和 deb 依賴項：

src/cartographer/scripts/install_proto3.sh

sudo rosdep init?? # if error message appears about file already existing, just ignore and continue

rosdep update

rosdep install --from-paths src --ignore-src --rosdistro=${ROS_DISTRO} -y

將機器人姿態發布(Robot Pose Publisher)程序包克隆到工作區中：

cd $HOME/catkin_ws/src

git clone https://github.com/GT-RAIL/robot_pose_publisher.git

使用你喜歡的編輯器（如“gedit”）創建 cartographer_ros 啟動文件

cd $HOME/catkin_ws/src/cartographer_ros/cartographer_ros/launch

gedit cartographer.launch

將以下內容復制粘貼到文件中：

<launch><param name="/use_sim_time" value="false" /><node name="cartographer_node"pkg="cartographer_ros"type="cartographer_node"args="-configuration_directory $(find cartographer_ros)/configuration_files -configuration_basename cartographer.lua"output="screen"><remap from="odom" to="/mavros/local_position/odom" /><remap from="imu" to="/mavros/imu/data" /></node><node name="cartographer_occupancy_grid_node"pkg="cartographer_ros"type="cartographer_occupancy_grid_node" /><node name="robot_pose_publisher"pkg="robot_pose_publisher"type="robot_pose_publisher"respawn="false"output="screen" ><param name="is_stamped" type="bool" value="true"/><remap from="robot_pose" to="/mavros/vision_pose/pose" /></node><node pkg="tf" type="static_transform_publisher" name="base_to_laser_broadcaster" args="0 0 0 0 0 0 base_link laser 100" />
</launch>

使用我們喜歡的編輯器（如“gedit”）創建 cartographer.lua 腳本：

cd $HOME/catkin_ws/src/cartographer_ros/cartographer_ros/configuration_files

gedit cartographer.lua

將以下內容復制粘貼到文件中。

include "map_builder.lua"
include "trajectory_builder.lua"options = {map_builder = MAP_BUILDER,trajectory_builder = TRAJECTORY_BUILDER,map_frame = "map",tracking_frame = "base_link",published_frame = "base_link",odom_frame = "odom",provide_odom_frame = true,publish_frame_projected_to_2d = false,use_odometry = false,use_nav_sat = false,use_landmarks = false,num_laser_scans = 1,num_multi_echo_laser_scans = 0,num_subdivisions_per_laser_scan = 1,num_point_clouds = 0,lookup_transform_timeout_sec = 0.2,submap_publish_period_sec = 0.3,pose_publish_period_sec = 5e-3,trajectory_publish_period_sec = 30e-3,rangefinder_sampling_ratio = 1.,odometry_sampling_ratio = 1.,fixed_frame_pose_sampling_ratio = 1.,imu_sampling_ratio = 1.,landmarks_sampling_ratio = 1.,
}MAP_BUILDER.use_trajectory_builder_2d = trueTRAJECTORY_BUILDER_2D.min_range = 0.05
TRAJECTORY_BUILDER_2D.max_range = 30
TRAJECTORY_BUILDER_2D.missing_data_ray_length = 8.5
TRAJECTORY_BUILDER_2D.use_imu_data = false
TRAJECTORY_BUILDER_2D.ceres_scan_matcher.translation_weight = 0.2
TRAJECTORY_BUILDER_2D.ceres_scan_matcher.rotation_weight = 5
TRAJECTORY_BUILDER_2D.use_online_correlative_scan_matching = true
TRAJECTORY_BUILDER_2D.real_time_correlative_scan_matcher.linear_search_window = 0.1
TRAJECTORY_BUILDER_2D.real_time_correlative_scan_matcher.translation_delta_cost_weight = 1.
TRAJECTORY_BUILDER_2D.real_time_correlative_scan_matcher.rotation_delta_cost_weight = 10
TRAJECTORY_BUILDER_2D.motion_filter.max_angle_radians = math.rad(0.2)
-- for current lidar only 1 is good value
TRAJECTORY_BUILDER_2D.num_accumulated_range_data = 1TRAJECTORY_BUILDER_2D.min_z = -0.5
TRAJECTORY_BUILDER_2D.max_z = 0.5POSE_GRAPH.constraint_builder.min_score = 0.65
POSE_GRAPH.constraint_builder.global_localization_min_score = 0.65
POSE_GRAPH.optimization_problem.huber_scale = 1e2
POSE_GRAPH.optimize_every_n_nodes = 30return options

！Note

與其手動修改上述軟件包，不如克隆該倉庫并安裝依賴包。